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Description

This update introduces the LLM Copilot Extension for Visual Studio Code, enhancing the coding experience by integrating a powerful language model directly within the IDE. The extension provides real-time code suggestions, auto-completion, and documentation assistance, enabling developers to write code more efficiently.

Fixes # (1587)

Type of change

  • Added a new machine learning frameworks, libraries or software.
  • Documentation update

Checklist:

  • My code follows the style guidelines of this project
  • I have performed a self-review of my own code
  • I have commented my code, particularly in hard-to-understand areas
  • I have made corresponding changes to the documentation
  • My changes generate no new warnings

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Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊

@Pratik-Tech-Wizard
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@sanjay-kv Please review and approve an appropriate label.

@sanjay-kv sanjay-kv merged commit 0a8768d into recodehive:main Oct 30, 2024
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@sanjay-kv
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can i know more about how does this work. and what is the use case. just curious to know about this
@Pratik-Tech-Wizard

@Pratik-Tech-Wizard
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The languages file works like :-
-Language Detection: The tool checks the file type (like .py for Python or .js for JavaScript) to know which programming language you’re using.
-Contextual Suggestions: Based on the detected language, it gives you helpful suggestions. For example, it might recommend useful libraries or show you common coding patterns.
-Integration with Frameworks: It knows about popular frameworks (like Flask for Python or React for JavaScript) and suggests relevant code snippets or best practices.

Use cases for this are Faster Coding, Learning Tool (it provides guidance and examples while you code), Better Code Quality, Easy Prototyping.

@sanjay-kv Kindly designate an appropriate label

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2 participants